Department of Critical Care Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
Department of Internal Medicine, Yiwu Maternity And Children Hospital, Yiwu, Zhejiang, China.
Front Endocrinol (Lausanne). 2024 Sep 16;15:1448314. doi: 10.3389/fendo.2024.1448314. eCollection 2024.
Sepsis is an inflammatory disease that leads to severe mortality, highlighting the urgent need to identify new therapeutic strategies for sepsis. Proteomic research serves as a primary source for drug target identification. We employed proteome-wide Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to identify potential targets for sepsis and sepsis-related death.
Genetic data for plasma proteomics were obtained from 35,559 Icelandic individuals and an initial MR analysis was conducted using 13,531 sepsis cases from the FinnGen R10 cohort to identify associations between plasma proteins and sepsis. Subsequently, significant proteins underwent genetic correlation analysis, followed by replication in 54,306 participants from the UK Biobank Pharma Proteomics Project and validation in 11,643 sepsis cases from the UK Biobank. The identified proteins were then subjected to colocalization analysis, enrichment analysis, and protein-protein interaction network analysis. Additionally, we also investigated a MR analysis using plasma proteins on 1,896 sepsis cases with 28-day mortality from the UK Biobank.
After FDR correction, MR analysis results showed a significant causal relationship between 113 plasma proteins and sepsis. Genetic correlation analysis revealed that only 8 proteins had genetic correlations with sepsis. In the UKB-PPP replication analysis, only 4 proteins were found to be closely associated with sepsis, while validation in the UK Biobank sepsis cases found overlaps for 21 proteins. In total, 30 proteins were identified in the aforementioned analyses, and colocalization analysis revealed that only 2 of these proteins were closely associated with sepsis. Additionally, in the 28-day mortality MR analysis of sepsis, we also found that only 2 proteins were significant.
The identified plasma proteins and their associated metabolic pathways have enhanced our understanding of the complex relationship between proteins and sepsis. This provides new avenues for the development of drug targets and paves the way for further research in this field.
败血症是一种炎症性疾病，导致严重的死亡率，突出表明迫切需要为败血症确定新的治疗策略。蛋白质组学研究是药物靶点识别的主要来源。我们采用蛋白质组学全基因组孟德尔随机化（MR）、遗传相关性分析和共定位分析来鉴定败血症和败血症相关死亡的潜在靶点。
从 35559 名冰岛个体中获取血浆蛋白质组学的遗传数据，并使用 FinnGen R10 队列中的 13531 例败血症病例进行初始 MR 分析，以鉴定血浆蛋白与败血症之间的关联。随后，对显著蛋白进行遗传相关性分析，随后在 UK Biobank Pharma Proteomics Project 的 54306 名参与者中进行复制，并在 UK Biobank 的 11643 例败血症病例中进行验证。然后对鉴定出的蛋白进行共定位分析、富集分析和蛋白质-蛋白质相互作用网络分析。此外，我们还使用来自 UK Biobank 的 1896 例败血症病例和 28 天死亡率的血浆蛋白进行了 MR 分析。
经过 FDR 校正，MR 分析结果显示 113 种血浆蛋白与败血症之间存在显著的因果关系。遗传相关性分析显示，只有 8 种蛋白与败血症具有遗传相关性。在 UKB-PPP 复制分析中，只有 4 种蛋白与败血症密切相关，而在 UK Biobank 败血症病例中进行验证时发现重叠的蛋白有 21 种。总共在上述分析中鉴定出 30 种蛋白，共定位分析显示只有 2 种蛋白与败血症密切相关。此外，在败血症的 28 天死亡率的 MR 分析中，我们也发现只有 2 种蛋白具有显著性。
鉴定出的血浆蛋白及其相关代谢途径增强了我们对蛋白质与败血症之间复杂关系的理解。这为药物靶点的开发提供了新的途径，并为该领域的进一步研究铺平了道路。
